Gathering the right kind and the right amount of information is crucial for any decision-making process. This book presents a unified framework for assessing the value of potential data gathering schemes by integrating spatial modelling and decision analysis, with a focus on the Earth sciences. The authors discuss the value of imperfect versus perfect information, and the value of total versus partial information, where only subsets of the data are acquired. Concepts are illustrated using a suite of quantitative tools from decision analysis, such as decision trees and influence diagrams, as well as models for continuous and discrete dependent spatial variables, including Bayesian networks, Markov random fields, Gaussian processes, and multiple-point geostatistics. Unique in scope, this book is of interest to students, researchers and industry professionals in the Earth and environmental sciences, who use applied statistics and decision analysis techniques, and particularly to those working in petroleum, mining, and environmental geoscience.
Jo Eidsvik is Professor of Statistics at the Norwegian University of Science and Technology (NTNU), Norway, and has previous industry work experience from the Norwegian Defense Research Establishment and Statoil. Tapan Mukerji is Associate Professor (Research) in the Department of Energy Resources Engineering and the Department of Geophysics at Stanford University. He is a co-author of The Rock Physics Handbook and Quantitative Seismic Interpretation. Debarun Bhattacharjya is Research Staff Member in the Cognitive Computing Research group at the IBM T. J. Watson Research Center, New York. He applies his expertise in decision analysis towards developing algorithms and tools for both research and consulting purposes.
Preface; 1. Introduction; 2. Statistical models and methods; 3. Decision analysis; 4. Spatial modeling; 5. Value of information in spatial decision situations; 6. Earth sciences applications; 7. Problems and projects; Appendix. Selected statistical models and sampling methods; References; Index.
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